Hongwen Dong

1.1k total citations · 1 hit paper
15 papers, 854 citations indexed

About

Hongwen Dong is a scholar working on Computer Vision and Pattern Recognition, Civil and Structural Engineering and Media Technology. According to data from OpenAlex, Hongwen Dong has authored 15 papers receiving a total of 854 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Vision and Pattern Recognition, 6 papers in Civil and Structural Engineering and 4 papers in Media Technology. Recurrent topics in Hongwen Dong's work include Infrastructure Maintenance and Monitoring (6 papers), Advanced Image Fusion Techniques (4 papers) and Industrial Vision Systems and Defect Detection (4 papers). Hongwen Dong is often cited by papers focused on Infrastructure Maintenance and Monitoring (6 papers), Advanced Image Fusion Techniques (4 papers) and Industrial Vision Systems and Defect Detection (4 papers). Hongwen Dong collaborates with scholars based in China and United Kingdom. Hongwen Dong's co-authors include Kechen Song, Yunhui Yan, Yu He, Jing Xu, Qinggang Meng, Yanyan Wang, Jie Liu, Defu Zhang, Hongkun Tian and Shuai Ma and has published in prestigious journals such as IEEE Transactions on Industrial Electronics, Expert Systems with Applications and IEEE Transactions on Intelligent Transportation Systems.

In The Last Decade

Hongwen Dong

14 papers receiving 840 citations

Hit Papers

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What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

PGA-Net: Pyramid Feature Fusion and Global Context Attention Network for Automated Surface Defect Detection

2019 379 citations Hongwen Dong, Kechen Song et al. IEEE Transactions on Industrial Informatics profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Hongwen Dong China	11	505	381	292	227	162	15	854
Ziji Ma China	15	148 0.3×	189 0.5×	215 0.7×	246 1.1×	122 0.8×	51	601
Menghui Niu China	12	281 0.6×	247 0.6×	196 0.7×	160 0.7×	117 0.7×	17	537
Guifang Duan China	15	236 0.5×	237 0.6×	75 0.3×	142 0.6×	90 0.6×	71	630
Ning Yan China	5	264 0.5×	172 0.5×	50 0.2×	107 0.5×	66 0.4×	9	438
Jingming Xie China	12	217 0.4×	171 0.4×	41 0.1×	176 0.8×	80 0.5×	52	547
Young Shik Moon South Korea	10	117 0.2×	309 0.8×	204 0.7×	65 0.3×	27 0.2×	59	624
Tzu-Yi Hung Singapore	10	143 0.3×	443 1.2×	47 0.2×	46 0.2×	150 0.9×	22	679
Qingsheng Xie China	7	146 0.3×	156 0.4×	65 0.2×	89 0.4×	32 0.2×	13	388
Junping Zhong China	8	149 0.3×	113 0.3×	141 0.5×	159 0.7×	18 0.1×	15	378

Countries citing papers authored by Hongwen Dong

Since Specialization

Citations

This map shows the geographic impact of Hongwen Dong's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Hongwen Dong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hongwen Dong more than expected).

Fields of papers citing papers by Hongwen Dong

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hongwen Dong. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Hongwen Dong. The network helps show where Hongwen Dong may publish in the future.

Co-authorship network of co-authors of Hongwen Dong

This figure shows the co-authorship network connecting the top 25 collaborators of Hongwen Dong. A scholar is included among the top collaborators of Hongwen Dong based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hongwen Dong. Hongwen Dong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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15 of 15 papers shown

Song, Kechen, et al.. (2023). Lightweight multi-level feature difference fusion network for RGB-D-T salient object detection. Journal of King Saud University - Computer and Information Sciences. 35(8). 101702–101702. 8 indexed citations

Song, Kechen, et al.. (2023). DCBFusion: an infrared and visible image fusion method through detail enhancement, contrast reserve and brightness balance. The Visual Computer. 40(8). 5763–5781.

Wang, Yanyan, Kechen Song, Menghui Niu, et al.. (2022). Unsupervised defect detection with patch-aware mutual reasoning network in image data. Automation in Construction. 142. 104472–104472. 16 indexed citations

Ma, Shuai, Kechen Song, Hongwen Dong, Hongkun Tian, & Yunhui Yan. (2022). Modal complementary fusion network for RGB-T salient object detection. Applied Intelligence. 53(8). 9038–9055. 34 indexed citations

Dong, Hongwen, et al.. (2021). Automatic Inspection and Evaluation System for Pavement Distress. IEEE Transactions on Intelligent Transportation Systems. 23(8). 12377–12387. 29 indexed citations

Dong, Hongwen, et al.. (2021). Deep Metric Learning-Based for Multi-Target Few-Shot Pavement Distress Classification. IEEE Transactions on Industrial Informatics. 18(3). 1801–1810. 82 indexed citations

Zhang, Defu, Kechen Song, Jing Xu, Hongwen Dong, & Yunhui Yan. (2021). An image-level weakly supervised segmentation method for No-service rail surface defect with size prior. Mechanical Systems and Signal Processing. 165. 108334–108334. 39 indexed citations

Bao, Yanqi, Kechen Song, Jie Wang, et al.. (2021). Visible and thermal images fusion architecture for few-shot semantic segmentation. Journal of Visual Communication and Image Representation. 80. 103306–103306. 17 indexed citations

Xu, Jing, Kechen Song, Defu Zhang, et al.. (2020). Informed Anytime Fast Marching Tree for Asymptotically Optimal Motion Planning. IEEE Transactions on Industrial Electronics. 68(6). 5068–5077. 20 indexed citations

10.

Wang, Yanyan, et al.. (2020). RENet: Rectangular convolution pyramid and edge enhancement network for salient object detection of pavement cracks. Measurement. 170. 108698–108698. 64 indexed citations

11.

Song, Kechen, et al.. (2020). NERNet: Noise estimation and removal network for image denoising. Journal of Visual Communication and Image Representation. 71. 102851–102851. 22 indexed citations

12.

Liu, Jie, Kechen Song, Yu He, et al.. (2020). Learning object-centric complementary features for zero-shot learning. Signal Processing Image Communication. 89. 115974–115974. 6 indexed citations

13.

Xu, Jing, Kechen Song, Hongwen Dong, & Yunhui Yan. (2019). A batch informed sampling-based algorithm for fast anytime asymptotically-optimal motion planning in cluttered environments. Expert Systems with Applications. 144. 113124–113124. 9 indexed citations

14.

Dong, Hongwen, Kechen Song, Yu He, et al.. (2019). PGA-Net: Pyramid Feature Fusion and Global Context Attention Network for Automated Surface Defect Detection. IEEE Transactions on Industrial Informatics. 16(12). 7448–7458. 379 indexed citations breakdown →

15.

He, Yu, Kechen Song, Hongwen Dong, & Yunhui Yan. (2019). Semi-supervised defect classification of steel surface based on multi-training and generative adversarial network. Optics and Lasers in Engineering. 122. 294–302. 129 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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